Challenges in the area of enterprise decision making is ever growing, and more so, on account of exponential growth in enterprise data and external sources. Monitoring and mining from various enterprise data sources presents challenges in view of unstructured and structured content spread across these data sources. Examples of unstructured and structured content may include, but is not limited to, data from emails, call centre transcripts, policy documents, broker submissions, bank statements, customer complaints, and loss run documents. Generating valuable insights from these data sources is increasingly being recognized as a necessity for enterprise decision making. As such, data and information retrieval, extraction, aggregation, and analysis has become a humungous and complex task. Yet further, there is an increasing demand for right data metrics catering to the requirements of enterprises which would influence strategy, products, and services of those enterprises.
In light of the above drawbacks, there is a need for a system and method that optimizes data aggregation and analytics across physical and digital data sources. Also, there is a need for a system and method that provides comprehensive, accurate, real-time and actionable insights across a plurality of enterprise data points spread over multiple physical and digital data sources.